The goal of this research is to understand how we see what we see: how does the brain analyze the light falling on the retina of the eye to reveal a world full of objects, people and things? During the past year we have focused on the perception of complex visual stimuli, in particular real-world visual scenes (NCT00001360). Perception of real world scenes: Real-world scenes are incredibly complex and heterogeneous, yet we are able to identify and categorize them effortlessly. While prior studies have identified three major brain regions that appear to be specialized for scene processing, it remains unclear what the precise roles of these different regions are and what information they contain. Building on a general framework for visual processing we proposed in the past few years, we have been investigating the basic properties of these three scene-selective regions and trying to elucidate how these three regions interact to enable us to understand the world before our eyes. In particular, we have been investigating the extent to which these regions can be explained in terms of encoding low level visual properties (e.g. contrast, color, edges) versus high level properties (e.g. objects, category, actions that can be performed in the depicted scene). One main area of focus has been the relationship between retinotopy (point-by-point mapping of the visual field onto the cortical surface of the brain) and category-selectivity (differential responses to images from different visual categories e.g. scenes versus faces). We evaluate retinotopy by presenting fragments of scenes to specific portions of the visual field and measure the response across the brain with functional magnetic resonance imaging (fMRI). Similarly, we measure category-selectivity by presenting images from different categories (e.g. faces, scenes, objects, bodies) and measuring the associated brain response. We find that there is no simple relationship between these two different organizational principles. Category-selective regions exhibit retinotopy, but individual category-selective regions overlap multiple maps. These results suggests that individual category-selective regions may contain multiple sub-regions within specific retinotopic maps that perform separate computations on the images. One of these scene-selective regions is found in medial parietal cortex and is often implicated in memory function and spatial navigation. Our data show that there may be a gradient of function within medial parietal cortex. Posterior regions show strong retinotopy and scene-selectivity and are most strongly connected with other regions of posterior visual cortex. In contrast anterior regions are much less retinotopic and scene-selective but show strong connectivity with regions of ventral temporal cortex and parietal cortex that are implicated in memory. In addition to studying how the representations of scenes are spatially distributed within the brain, we have also been examining the time course of visual scene processing using electroencephalography (EEG). In contrast to fMRI, which has good spatial but poor temporal resolution, EEG allows us to monitor brain activity at a millisecond resolution. These experiments have revealed that scene-selective activity and representation of specific scene properties such as naturalness, is not observed until approximately 200 milliseconds after the onset of a scene picture, much later then the initial visual response. Collectively these results provide important insights into the brain network that is involved in processing real-world visual scenes and we have recently developed a specific framework for thinking about the distributed processing of scenes within visual cortex. We are currently evaluating the specific roles of scene-selective regions by i) using transcranial magnetic stimulation (or TMS) to temporarily disrupt their function and observe the impact on behavior; ii) comparing explicit computational and theoretical models of scene representation with the representations observed in different parts of the brain. Elucidating how the brain enables us to recognize objects, scenes, faces and bodies provides important insights into the nature of our internal representations of the world around us. Understanding these representations is vital in trying to determine the underlying deficits in many mental health and neurological disorders.